Next Article in Journal
Ferroptosis: Cancer Stem Cells Rely on Iron until “to Die for” It
Next Article in Special Issue
Drosophila Heart as a Model for Cardiac Development and Diseases
Previous Article in Journal
Rho GTPases in Skeletal Muscle Development and Homeostasis
Previous Article in Special Issue
Chemical Genetic Screen in Drosophila Germline Uncovers Small Molecule Drugs That Sensitize Stem Cells to Insult-Induced Apoptosis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

In-Depth Annotation of the Drosophila Bithorax-Complex Reveals the Presence of Several Alternative ORFs That Could Encode for Motif-Rich Peptides

IGFL, ENS-Lyon, 32/34 Av. Tony Garnier, 69007 Lyon, France
*
Author to whom correspondence should be addressed.
Cells 2021, 10(11), 2983; https://doi.org/10.3390/cells10112983
Submission received: 13 September 2021 / Revised: 17 October 2021 / Accepted: 26 October 2021 / Published: 2 November 2021
(This article belongs to the Special Issue Drosophila: A Model for Genetic Research)

Abstract

:
It is recognized that a large proportion of eukaryotic RNAs and proteins is not produced from conventional genes but from short and alternative (alt) open reading frames (ORFs) that are not captured by gene prediction programs. Here we present an in silico prediction of altORFs by applying several selecting filters based on evolutionary conservation and annotations of previously characterized altORF peptides. Our work was performed in the Bithorax-complex (BX-C), which was one of the first genomic regions described to contain long non-coding RNAs in Drosophila. We showed that several altORFs could be predicted from coding and non-coding sequences of BX-C. In addition, the selected altORFs encode for proteins that contain several interesting molecular features, such as the presence of transmembrane helices or a general propensity to be rich in short interaction motifs. Of particular interest, one altORF encodes for a protein that contains a peptide sequence found in specific isoforms of two Drosophila Hox proteins. Our work thus suggests that several altORF proteins could be produced from a particular genomic region known for its critical role during Drosophila embryonic development. The molecular signatures of these altORF proteins further suggests that several of them could make numerous protein–protein interactions and be of functional importance in vivo.
Keywords:
lncRNA; smORF; altORF; ELM; SLiM

1. Introduction

Classical gene prediction programs are based on automated intron–exon annotations and comparison with cDNA sequences and/or genes from different organisms [1,2,3,4]. These computational methods led to the general finding that a surprisingly small fraction of the eucaryotic sequenced genomes (2/3% on average) corresponds to protein-encoding open reading frames (ORFs, [5]). The small number of these so-called “conventional” genes is in sharp contrast with the biological complexity of multicellular organisms [6]. Moreover, a large proportion of the genome was observed to be transcribed outside the conventional genes [5], suggesting that non-canonical coding sequences could escape detection from genome annotation pipelines. This non-conventional transcriptome, also assigned as non-coding (nc) RNAs, has for a long time been considered to be a transcriptional noise product [7]. ncRNAs are by now recognized as acting as various categories of RNA molecules (such as nucleolar-RNAs, enhancer-RNAs, circular-RNAs, micro-RNAs and long-ncRNAs) and to mediate fundamental cellular processes, including transcription and translation efficiency or mRNA stability [8,9,10,11,12,13]. Along the same line, mass spectrometry (MS)-based approaches systematically revealed that a significant proportion of the sequenced peptides did not match annotated proteins [14,15,16]. Most of these peptides originated from proteins that contained less than 100 residues (below the minimal length for a conventional protein) and could be produced from ORFs that do not contain an AUG-start codon or an optimal Kozak sequence [17,18,19]. These small ORFs (smORFs, also referred to as shortORFs, sORFs) are found in non-coding regions (ncRNAs and 5′ or 3′UTRs of mRNAs) and represent a large proportion of the transcriptome [20]. smORFs have also been called upstream ORFs (uORFs) when present in the 5′UTR region, with a general (but not exclusive, see also: [21,22]) role in the transcriptional and translational control of the associated downstream conventional ORF [23,24,25]. Bioinformatics analyses dedicated to smORFs in the plant Arabidopsis [26], yeast Saccharomyces [27] and fruit fly Drosophila [28] further predicted that smORFs could account for 3% to 5% of the protein-coding genes.
Because of their size, low abundance in the cell and more generally lack of tools (e.g., antibodies), a quite limited number of small peptides has been characterized at both the molecular and functional level in plant and animal species. A pioneer work showed that a small peptide of 71 residues, Polar granule component (Pgc), was critical to inhibit the somatic transcriptional program in Drosophila germ cells by forbidding the recruitment of a particular kinase that is necessary to activate the RNA polymerase II [29]. Other small peptides produced in Drosophila have been shown to regulate the activity of the transcription factor Shaven baby (Svb). These peptides, called Polished rice (Pri) or Tarsal-less (Tal), are synthesized from four altORFs of different sizes (ranging from 11 to 32 codons) and promote the cleavage of a N-terminal repressor domain in Svb. This removal allows Svb to activate the set of target genes involved in the formation of trichomes in the larval cuticle [30]. Pri/Tal peptides are also involved in the regulation of other developmental aspects in Drosophila [31]. Another alternative micropeptide produced from a lncRNA of the Drosophila Bithorax-complex (BX-C), called MSAmiP, has recently been described to be expressed in the male accessory glands, which produce a seminal fluid that is critical for controlling the postmating response of the female [32]. These examples illustrate the emerging and probably highly diverse molecular roles of non-conventional ORFs in vivo.
Accordingly, ribosome profiling analyses [33,34], together with the re-annotation of transcriptomes (based on algorithm for ORF prediction from transcriptions sequences) to re-analyze proteomic datasets [34,35], confirmed that several non-conventional mRNAs could lead to the production of proteins. For example, the re-annotation of proteomic datasets showed that as many as 174 771 non-conventional ORFs coding for 71 705 proteins could exist in Drosophila [35]. These observations definitively established the importance of considering non-conventional ORFs to better understand the basic products of the genome. The re-annotation analyses also revealed a novel category of non-conventional ORFs that has been called “alternative ORFs” (altORFs). In contrast to smORFs, altORFs encode for peptides that resemble more to canonical proteins in terms of genomic marks for synthesis (such as an ATG start codon and a Kozak sequence). They are also longer than 30 codons (and can be longer than 100 codons) and can be located on ncRNAs, in UTRs or in different reading frames from annotated CDSs in mRNAs [35,36].
Here, we describe a novel in silico prediction of altORFs that is specifically dedicated to Drosophila BX-C. Our extensive manual annotation was performed using stringent filtering criteria for sequence conservation and for genomic marks’ scores deduced from previously described altORF peptides (Aspden et al., 2014). Our goal was to propose a high-confidence list of altORFs, and to assess whether the selected altORFs could encode for potential functional proteins. To this end, we looked at several protein signatures such as the global structure or the presence of short interaction motifs.
Altogether, our work revealed that several alternative proteins of variable size, structure, and motif contents could be produced from different regions of BX-C. We propose that the critical role of BX-C during embryonic development could not only rely on the currently characterized lncRNAs and Hox genes but also on several and so far unexplored altORFs.

2. Materials and Methods

2.1. altORF Prediction

altORFs were predicted in the whole BX-C locus of D. melanogaster (chr3R:12,481,489-12,801,607 in dm3 assembly) and in orthologous regions of D. simulans (droSim1), D. sechellia (droSec1), D. yakuba (droYak2), D. erecta (droEre1), D. ananassae (droAna2), D. pseudoobscura (dp3), D. persimilis (droPer1), D. mojavensis (droMoj2), D. virilis (droVir2) and D. grimshawi (droGri1) identified with blastn. This region spans ca. 320 kb.
altORFs were identified on both strands using a home-made BioPython script requiring a minimal length of 30 amino acids. Briefly, this script searches for sequences longer than 90 nucleotides, beginning with an ATG and with no interruption by a stop codon. It sorts out the corresponding translated sequences. The full script can be provided upon request.

2.2. altORF Characterization

2.2.1. Orthology and Age

Orthologous altORFs were identified between species by all-by-all peptides comparison using BlastP with default parameters and by requiring a maximum E-value of 1 × 10−5. Although a tBlastn search could have been more sensitive to detect orthologous sequences, it was not applied since it could not discriminate between altORF-containing and non-altORF-containing sequences. The minimal age of each ORF was deduced from the divergence time of the two most distant species in which it was found. Species divergence times were retrieved from [37].

2.2.2. Nucleotidic Conservation

Conservation of the DNA sequences encoding the ORFs was computed from the PhastCons 15-way track available at UCSC, which evaluates evolutionary conservation in 12 Drosophila species, mosquito, honeybee and red floor beetle based on a phylogenetic hidden Markov model [38].
dN/dS ratios were computed for the final list of 48 altORFs using PAML [39]. Calculation was based on multiple alignments obtained with Muscle [40] and a phylogenetic tree reconstructed with PhyML [41] with the following parameters: Model-given amino acid equilibrium frequencies, no invariable sites, optimized across site rate variation, NNI tree searching, and BioNJ starting trees with optimized tree topology. Parameters for dN/dS calculation can be provided upon request (codeml.ctl). dN/dS must be taken with caution when dS < 0.01 (sequences too close, with not enough divergence) or dS > 2 (sequences too divergent).

2.2.3. Transcription and Translation Features

Transcription promoters were predicted in the whole D. melanogaster BX-C region using the Neural Network Promoter Prediction program available on the Berkeley Drosophila Genome Project (BDGP) website (https://www.fruitfly.org/seq_tools/promoter.html, Reese 2001, last accessed on 14 October 2021), with default parameters. altORFs were attributed the closest upstream promoter, annotated by the intervening distance and its prediction score.
PolyA sites were searched in 150 nt downstream of the altORF in all the species were it was found using the PolyA_SVM program [42].
altORF expression was assessed in 8–10 h whole embryos by blasting them against RNA-seq data retrieved from modENCODE (SRX008010, SRX008249, SRX008252, SRX008273, and SRX008274 experiences). This stage was voluntary chosen to restrict the analysis and identification of altORFs that could potentially and specifically act with the Hox genes during their early patterning functions in the embryonic epidermis.
Kozak sequences were retrieved for each predicted altORF, and their relative strength was assigned according to [43].

2.2.4. Overlap of altORFs with Other Genomic Features

Gene annotations (transcripts, exons, CDS) were retrieved from FlyBase (https://flybase.org/, accessed on 10 March 2015) and overlapped with DroMel altORF coordinates. DroMel altORFs were also overlapped with cDNAs retrieved from ModENCODE (http://www.modencode.org/, accessed on 5 August 2015), in sense or antisense orientation. altORF peptide sequences were finally compared to protein sequences Ubx, AbdA, or AbdB using BlastP to identify altORFs in frame with Hox coding sequences.
Transposable element annotations were retrieved from the Natural Transposable Element Project of the BDGP website (https://www.fruitfly.org/p_disrupt/TE.html, version 9.4.1. accessed on 17 September 2015), and overlapped with altORF coordinates.
Predicted altORFs were finally compared with different sets of peptides already published in the literature, including peptides from the PeptideAtlas database (http://www.peptideatlas.org/, last accessed on 14 October 2021), from Poly-ribo-seq approach [33], proteomic datasets [35], and smORFs [28].

2.3. Characterization of the Predicted Peptides

Predicted peptides were submitted to InterProScan (https://www.ebi.ac.uk/interpro/search/sequence/, last accessed on 3 October 2015) to search for putative conserved protein domains such as signal peptides or transmembrane helix. Potential signal peptides were predicted using the SignalP-5.0 Server [44] (http://www.cbs.dtu.dk/services/SignalP/, last accessed on 13 October 2015). Transmembrane helices were predicted using the TMHMM Server v. 2.0 [45] (http://www.cbs.dtu.dk/services/TMHMM/, last accessed on 13 October 2015).
Intrinsically disordered regions were predicted using UIPred2A server (https://iupred2a.elte.hu/plot_new, [46], last accessed on 11 May 2021).
Predicted altORF peptides were also compared to the full proteome by submitting them to a BlastP search against the nr database, with default parameters.
Eukaryotic Linear Motifs (ELMs) were identified using the ELM database (http://elm.eu.org/, last accessed on 7 June 2021) and FuzzPro (https://www.bioinformatics.nl/cgi-bin/emboss/fuzzpro, last accessed on 26 October 2015). The search was restricted to ELMs found in one of Ubx, AbdA, or AbdB proteins. All ELMs found in each altORF are given in Table S1. Description of ELMs found in Ubx, AbdA, and/or AbdB is given in Table S2.
A global “ELM score” was computed, for each ORF, as follows:
E L M s c o r e O R F i = ( j ( m o t i f s j in O R F i / m o t i f s j in a l l O R F s ) / a m i n o a c i d l e n g t h o f O R F i ) × 10 6
This score attempts to quantify the mean occurrence of ELMs in each altORF by taking into account the length of the altORF as well as the frequency of each ELM in all the predicted altORFs.

3. Results and Discussion

3.1. Annotation of altORFs in BX-C

We have considered the 320 kb region of BX-C and applied a home-made BioPython script (see materials and methods) to search for all possible altORFs with two required criteria for altORFs: a minimal length of 30 codons and an ATG start codon [36]. In contrast to the previous annotations of altORFs, our prediction analysis was not restricted to ncRNAs and mRNAs (therefore considering the entire intergenic regions). This first step led to the prediction of 2086 altORFs (Figure 1A and Figure 2). We next considered altORFs that were not matching the conventional proteins Ultrabithorax (Ubx), Abdominal-A (AbdA) or Abdominal-B (AbdB) to discard altORFs that could correspond to any Hox isoform, achieving 2075 predicted altORFs in total (Figure 1A,B). In the second and third filtering steps, we arbitrarily decided that altORFs should be present in at least two different Drosophila species that are distanced by 10 M years or more during evolution (Figure 1A–C). These parameters allowed us to select evolutionary conserved altORFs, leading to a list of 1233 predicted altORFs (Figure 1A). To further increase the evolutionary confidence score, we analyzed the 1233 altORFs with PhastCons ([38] and materials and methods) and applied a threshold value based on the scores found with altORFs identified from previous genome annotation analyses [33,35] in our list (these scores are highlighted in red in Table 1). Several of these previously annotated altORFs have been confirmed by tandem mass spectrometry (MS/MS) in human [35] or Drosophila [33] cell lines, or by a sensitive ribosome footprinting approach called ‘Poly-ribo-seq’ in Drosophila S2 cells [33], underlining that their genome annotation scores could serve as a reference value for filtering altORF peptides with a higher synthesis probability. Of note, we could not use reference values from altORF peptides captured by proteomics approach and specifically located in BX-C: no MS/MS-captured altORF peptide is present in BX-C (https://openprot.org/p/browse, accessed on 1 October 2021) and the Poly-ribo-seq data could not be exploited in the context of BX-C since this genomic region is under strong transcriptional repressive state in S2 cells (these cells do not express any Hox gene; [47] and Supplementary Figure S1). In conclusion, the PhastCons threshold value deduced from the previously annotated altORFs present in our list was 0.43 and this threshold was therefore applied to further filter our list, leading to 1150 predicted altORFs in BX-C (Figure 1A,B and Table 1).
Scores based on previously identified altORF peptides from genome annotation [33,35] present in the list and used for establishing the threshold values are highlighted in red.
The next filtering steps were based on genomic marks for transcription and translation. The selection filters were also deduced from the scores found with previously identified altORFs [33,35] present in our list. More precisely, we found that the promoter could not be located more than 278 nucleotides upstream of the start codon (ORF268 and ORFas200: Table 1) and we thus discarded all predicted altORFs that had a promoter located at higher distances from the first ATG. Along the same line, the minimum confidence score for the predicted promoter of previously identified altORFs of our list was 0.81 (Table 1), and we therefore did not consider altORFs that had a score below this value. Together, these two criteria (see also materials and methods) allowed us to restrict the list to 572 altORFs (Figure 1A,B). The next step consisted of applying a minimum score for the Kozak sequence (see materials and methods), which led to a list of 492 predicted altORFs (Figure 1A,B). Because the majority of the previously identified altORFs in this list did not show a relevant score for poly-adenylation sites (see materials and methods and Table S1), we did not consider this parameter for a selection step. The list was then submitted to RNA-seq data scores, using reference thresholds found with previously identified altORFs: altORFs should have a minimum number of 5 reads over at least 40% of their length (Table 1, Figure 1A,B and Material and Methods). Here, we only considered RNA-seq data of stage 8–10 h embryos for considering the number of reads, which is a stage of high RNA expression and during which Hox genes are specifying the epidermis along the anterior-posterior axis. The rational was to identify altORFs that could potentially be involved in these early Hox patterning functions. The reference threshold for altORF covering by RNA-seq was deduced by considering both S2 cells and stage 8–10 h embryos. These last filtering steps led to a final list of 48 altORFs for which we also calculated the dN/dS ratio (i.e., the ratio of non-synonymous mutations on synonymous ones, a value smaller than 1 testifying for a negative selection pressure) to assess whether they were under purifying selection. The score indicated a negative selection (dN/dS < 1) for 74% of ORFs for which the calculation could be performed (with sequences that were not too similar (dS < 0.01) or too divergent (dS > 2): Table S1 and materials and methods).
Altogether, our filtering criteria eliminated more than 98% of the altORFs present in the initial list (2038/2086 altORFs have been discarded). The remaining 48 altORFs display conservation, transcriptional, and translational scores that are comparable with the scores found with previously predicted altORF peptides. We therefore considered the 48 altORFs with a high-confidence protein synthesis potential.

3.2. Structure/Motifs Predictions of Conserved Alternative Peptides of BX-C

The majority of the 48 selected altORFs are in Ubx, abdA or AbdB (for almost half of them), the rest being equally present in lncRNAs or intergenic sequences (Figure 2). They are also of highly variable size, from 30 to 274 codons, highlighting that they could encode for proteins with a comparable size to the conventional ones (Table 1).
To assess whether the predicted altORFs could encode for peptides with potential molecular functions, we looked at several protein signatures. First, we observed that there was not a strict rule regarding the global structure (see also material and methods). Although the majority (28/48) displays a global ordered structure, several altORFs are also predicted as globally disordered or with a mixture of ordered and disordered regions (Table 1 and Supplementary Figures S2–S4).
No conserved domains were found in the 48 altORF proteins (see material and methods), but 6 altORFs encode for a protein containing a predicted transmembrane helix (ORF268, ORFas452, ORFas561, ORFas566, ORFas293, ORFas1009: Table 1 and Supplementary Figures S5–S8). This protein feature has been shown to be enriched in altORFs [33]. It is interesting to note that one of these altORFs has been characterized in a pioneer analysis of Ubx genomic sequences [48]. This altORF, named ORF268, is located in the 5′UTR region of Ubx and encodes for a 71 aa-long peptide that has been predicted in several previous studies [33,35]. It also contains a signal peptide and a transmembrane helix (Figure 3). This altORF peptide therefore constitutes a very good candidate for future functional analyses in vivo. In particular, it would be interesting to know whether it could modulate the expression and/or function of Ubx given its genomic localization.
We next looked at the presence of Eukaryotic Linear Motifs (ELMs, also called short linear motifs, SLiMs), which have been classified in different types depending on their interaction properties and characterized functions [49]. Here, we focused on ELMs that were found in Ubx, AbdA and/or AbdB (Table S2). We noticed that the large majority of previously captured altORF proteins of our list (11/15) had 4 or more ELMs of different types (Table 1 and Table S1). The ORF44, which is in the first exon of the AbdB-m isoform (but in a different frame), is an extreme example with 125 ELMs belonging to 17 different types (Table 1 and Table S1 and Figure 4). These observations suggest that altORF-derived proteins have a general tendency to be rich in ELMs. Accordingly, we observed the same tendency with the other altORFs of our selected list (only 3 out of the 33 remaining altORF peptides have less than 2 ELMs: Table 1).
To better evaluate the number of ELMs independently of the protein size and the intrinsic complexity of each ELM, we established an ELM score that takes into account the number of ELMs present in the altORF compared to the total number of ELMs found in the initial 2086 predicted altORFs and reported to the size of the corresponding altORF protein (see materials and methods). This ELM score was weak (below 100) for few altORF proteins (8/48, two of which corresponding to previously predicted altORF proteins (ORF682 and ORF817): Table 1). A high (between 100 to 200: 19/48 altORFs) to very high (above 200: 21/48) score was found for the majority of our predicted altORFs. These scores underline that the number of ELMs is not directly linked to the length of the altORF protein and is therefore of potential significance. Interestingly, we found that a set of conventional ORFs with a range of sizes similar to our 48 selected altORFs displayed a comparable ELM score distribution (Table S3). This observation underlines that a high ELM score is a hallmark of conventional proteins (as previously described: [50]) that is also found in our selected altORF peptides.
Several of these ELMs are largely distributed (like the USP7 binding motif or WW domain ligands motif; Table S2), but others are more restricted, such as the SCF ubiquitin ligase binding phosphodegrons motif, which is found in AbdA and three altORFs in total (ORFs as430, 211, and 44; Table S2), or the Cks1 ligand motif, which is found in AbdA and AbdB and five altORFs in total (ORFs as430, 211, 861, 389, and 44; Table S2). Whether the common presence of more specific ELMs could be more significative of a common molecular function remains to be investigated. It is also interesting to note that two ELMs present in Ubx, AbdA and/or AbdB were never found in the 48 selected altORFs (the CtBP ligand motif and sumoylation site, Table S2).
Finally, although we did not find any altORF with a significant score for conserved domains, one altORF, ORF682, contained a peptide sequence of 30 residues that is also found in the C-terminus of particular isoforms of Deformed (Dfd) and Sex combs reduced (Scr; Figure 5). The ORF682 is present in the coding sequence of Ubx (not in the same frame), has previously been predicted (Aspden et al., 2014), and encodes for a 60 aas long disordered protein that displays a reasonable ELM score (with two different ELMs outside the sequence found in Dfd and Scr: Figure 5 and Table 1). The presence of a common sequence between ORF682, Dfd and Scr is intriguing and suggests that it could mediate a common molecular function in the three proteins.

4. Conclusions

Our study revealed the presence of 48 altORFs with a high potential to encode for functional alternative proteins in BX-C. Probably many more non-conventional protein-encoding ORFs are present in BX-C. For example, our stringent selection criteria did not allow retrieving all previously predicted altORF proteins (Figure 1 and https://openprot.org/, last accessed on 18 October 2021), highlighting that alternative proteins could be less conserved within the Drosophila evolutionary tree and/or produced using more flexible genomic annotation marks. Along the same line, we did not consider smORFs. For example, 5098 smORFs with a minimal size of 10 codons could be predicted in BX-C. Several of those predicted smORFs could likely encode for small peptides, as described for MSAmiP [32].
Several of our 48 predicted altORF proteins contain molecular features that are highly suggestive of putative functions in vivo. These include the presence of a transmembrane helix or a general propensity to contain several ELMs. However, the molecular versatility of ELMs [51] does not allow the prediction of the precise molecular function of the altORFs, or whether a functional link could exist with Hox or any other specific protein in vivo. In any case, our work confirms the extraordinary potential for the genome to produce several alternative proteins. By restricting to a specific genomic region, it also identifies high-confidence altORFs (such as the ORF268) for future molecular and functional analyses in Drosophila.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/cells10112983/s1, Figure S1: Genome region covering BX-C and depicting the binding of the repressive state chromatin protein Polycomb (Pc, black bar) and RNA-seq (red peaks) in S2 cells, Figure S2: Examples of IUPred profiles of globally ordered altORFs, Figure S3: Examples of IUPred profiles of globally disordered altORFs, Figure S4: Examples of IUPred profiles of altORFs displaying both ordered and disordered regions, Figure S5: Characterization of the ORFas452, Figure S6: Characterization of the ORFas561, Figure S7: Characterization of the ORFas566, Figure S8: Characterization of the ORFas293, Table S1: List of the 48 selected altORFs following the different filtering steps based on conservation, transcription and translational marks criteria, Table S2: List of all ELMs presentfound in Ubx, AbdA and AbdB and found in the 48 selected altORF peptides, Table S3: List of all ELMs present in Ubx, AbdA and AbdB and found in conventional ORFs identified within and outside BX-C.

Author Contributions

Conceptualization, S.M.; methodology, S.M. and M.N.; software, M.N.; formal analysis, M.N.; investigation, S.M. and M.N.; writing—original draft preparation, S.M. and M.N.; writing—review and editing, S.M. and M.N.; supervision, S.M.; funding acquisition, S.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Predicted ORFs from [35] are available on https://www.roucoulab.com/p/downloads (accessed on 1 October 2021) with no restrictions. Predicted ORFs from [33] are publicly available in the Gene Expression Omnibus (GEO) database under accession GSE60384.

Acknowledgments

We thank Benoît Vanderperre for helpful comments on the manuscript and Jean-Nicolas Volff for early discussions on the project. Work in the laboratory of S.M. is supported by the Centre National de la recherche Scientifique (CNRS), Ecole Normale Supérieure (ENS) de Lyon, Association pour la Recherche sur le Cancer (ARC), Région Auvergne-Rhône-Alpes and Institut National du Cancer (InCA).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brent, M.R. Genome annotation past, present, and future: How to define an ORF at each locus. Genome Res. 2005, 15, 1777–1786. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Brent, M.R. Steady progress and recent breakthroughs in the accuracy of automated genome annotation. Nat. Rev. Genet. 2008, 9, 62–73. [Google Scholar] [CrossRef]
  3. Windsor, A.J.; Mitchell-Olds, T. Comparative genomics as a tool for gene discovery. Curr. Opin. Biotechnol. 2006, 17, 161–167. [Google Scholar] [CrossRef] [PubMed]
  4. Sleator, R.D. An overview of the current status of eukaryote gene prediction strategies. Gene 2010, 461, 1–4. [Google Scholar] [CrossRef] [PubMed]
  5. Djebali, S.; Davis, C.A.; Merkel, A.; Dobin, A.; Lassmann, T.; Mortazavi, A.; Tanzer, A.; Lagarde, J.; Lin, W.; Schlesinger, F.; et al. Landscape of transcription in human cells. Nature 2012, 489, 101–108. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Taft, R.J.; Pheasant, M.; Mattick, J.S. The relationship between non-protein-coding DNA and eukaryotic complexity. BioEssays 2007, 29, 288–299. [Google Scholar] [CrossRef]
  7. Kung, J.T.Y.; Colognori, D.; Lee, J.T. Long Noncoding RNAs: Past, Present, and Future. Genetics 2013, 193, 651–669. [Google Scholar] [CrossRef] [Green Version]
  8. Wright, M.W.; Bruford, E.A. Naming “junk”: Human non-protein coding RNA (ncRNA) gene nomenclature. Hum. Genom. 2011, 5, 90. [Google Scholar] [CrossRef] [Green Version]
  9. Statello, L.; Guo, C.-J.; Chen, L.-L.; Huarte, M. Gene regulation by long non-coding RNAs and its biological functions. Nat. Rev. Mol. Cell Biol. 2021, 22, 96–118. [Google Scholar] [CrossRef]
  10. Kristensen, L.S.; Andersen, M.S.; Stagsted, L.V.W.; Ebbesen, K.K.; Hansen, T.B.; Kjems, J. The biogenesis, biology and characterization of circular RNAs. Nat. Rev. Genet. 2019, 20, 675–691. [Google Scholar] [CrossRef]
  11. Ye, R.; Cao, C.; Xue, Y. Enhancer RNA: Biogenesis, function, and regulation. Essays Biochem. 2020, 64, 883–894. [Google Scholar] [CrossRef]
  12. Orr, M.W.; Mao, Y.; Storz, G.; Qian, S.-B. Alternative ORFs and small ORFs: Shedding light on the dark proteome. Nucleic Acids Res. 2020, 48, 1029–1042. [Google Scholar] [CrossRef]
  13. Nakamura, A.; Amikura, R.; Mukai, M.; Kobayashi, S.; Lasko, P.F. Requirement for a Noncoding RNA in Drosophila Polar Granules for Germ Cell Establishment. Science 1996, 274, 2075–2079. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Koenig, T.; Menze, B.H.; Kirchner, M.; Monigatti, F.; Parker, K.C.; Patterson, T.; Steen, J.J.; Hamprecht, F.A.; Steen, H. Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics. J. Proteome Res. 2008, 7, 3708–3717. [Google Scholar] [CrossRef]
  15. Vanderperre, B.; Lucier, J.-F.; Bissonnette, C.; Motard, J.; Tremblay, G.; Vanderperre, S.; Wisztorski, M.; Salzet, M.; Boisvert, F.-M.; Roucou, X. Direct Detection of Alternative Open Reading Frames Translation Products in Human Significantly Expands the Proteome. PLoS ONE 2013, 8, e70698. [Google Scholar] [CrossRef] [Green Version]
  16. Prabakaran, S.; Hemberg, M.; Chauhan, R.; Winter, D.; Tweedie-Cullen, R.Y.; Dittrich, C.; Hong, E.; Gunawardena, J.; Steen, H.; Kreiman, G.; et al. Quantitative profiling of peptides from RNAs classified as noncoding. Nat. Commun. 2014, 5, 5429. [Google Scholar] [CrossRef] [PubMed]
  17. Menschaert, G.; Van Criekinge, W.; Notelaers, T.; Koch, A.; Crappé, J.; Gevaert, K.; Van Damme, P. Deep Proteome Coverage Based on Ribosome Profiling Aids Mass Spectrometry-based Protein and Peptide Discovery and Provides Evidence of Alternative Translation Products and Near-cognate Translation Initiation Events*. Mol. Cell. Proteomics 2013, 12, 1780–1790. [Google Scholar] [CrossRef] [Green Version]
  18. Slavoff, S.A.; Mitchell, A.J.; Schwaid, A.G.; Cabili, M.N.; Ma, J.; Levin, J.Z.; Karger, A.D.; Budnik, B.A.; Rinn, J.L.; Saghatelian, A. Peptidomic discovery of short open reading frame–encoded peptides in human cells. Nat. Chem. Biol. 2013, 9, 59–64. [Google Scholar] [CrossRef] [Green Version]
  19. Delcourt, V.; Staskevicius, A.; Salzet, M.; Fournier, I.; Roucou, X. Small Proteins Encoded by Unannotated ORFs are Rising Stars of the Proteome, Confirming Shortcomings in Genome Annotations and Current Vision of an mRNA. Proteomics 2018, 18, 1700058. [Google Scholar] [CrossRef] [PubMed]
  20. Andrews, S.J.; Rothnagel, J.A. Emerging evidence for functional peptides encoded by short open reading frames. Nat. Rev. Genet. 2014, 15, 193–204. [Google Scholar] [CrossRef]
  21. Hayden, C.A.; Bosco, G. Comparative genomic analysis of novel conserved peptide upstream open reading frames in Drosophila melanogaster and other dipteran species. BMC Genom. 2008, 9, 61. [Google Scholar] [CrossRef] [Green Version]
  22. Renz, P.F.; Valdivia-Francia, F.; Sendoel, A. Some like it translated: Small ORFs in the 5′UTR. Exp. Cell Res. 2020, 396, 112229. [Google Scholar] [CrossRef]
  23. Johnstone, T.G.; Bazzini, A.A.; Giraldez, A.J. Upstream ORFs are prevalent translational repressors in vertebrates. EMBO J. 2016, 35, 706–723. [Google Scholar] [CrossRef] [Green Version]
  24. Chew, G.-L.; Pauli, A.; Schier, A.F. Conservation of uORF repressiveness and sequence features in mouse, human and zebrafish. Nat. Commun. 2016, 7, 11663. [Google Scholar] [CrossRef]
  25. Calvo, S.E.; Pagliarini, D.J.; Mootha, V.K. Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans. Proc. Natl. Acad. Sci. USA 2009, 106, 7507–7512. [Google Scholar] [CrossRef] [Green Version]
  26. Hanada, K.; Higuchi-Takeuchi, M.; Okamoto, M.; Yoshizumi, T.; Shimizu, M.; Nakaminami, K.; Nishi, R.; Ohashi, C.; Iida, K.; Tanaka, M.; et al. Small open reading frames associated with morphogenesis are hidden in plant genomes. Proc. Natl. Acad. Sci. USA 2013, 110, 2395–2400. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Kastenmayer, J.P. Functional genomics of genes with small open reading frames (sORFs) in S. cerevisiae. Genome Res. 2006, 16, 365–373. [Google Scholar] [CrossRef] [Green Version]
  28. Ladoukakis, E.; Pereira, V.; Magny, E.G.; Eyre-Walker, A.; Couso, J. Hundreds of putatively functional small open reading frames in Drosophila. Genome Biol. 2011, 12, R118. [Google Scholar] [CrossRef] [Green Version]
  29. Hanyu-Nakamura, K.; Sonobe-Nojima, H.; Tanigawa, A.; Lasko, P.; Nakamura, A. Drosophila Pgc protein inhibits P-TEFb recruitment to chromatin in primordial germ cells. Nature 2008, 451, 730–733. [Google Scholar] [CrossRef] [Green Version]
  30. Zanet, J.; Benrabah, E.; Li, T.; Pelissier-Monier, A.; Chanut-Delalande, H.; Ronsin, B.; Bellen, H.J.; Payre, F.; Plaza, S. Pri sORF peptides induce selective proteasome-mediated protein processing. Science 2015, 349, 1356–1358. [Google Scholar] [CrossRef]
  31. Galindo, M.I.; Pueyo, J.I.; Fouix, S.; Bishop, S.A.; Couso, J.P. Peptides Encoded by Short ORFs Control Development and Define a New Eukaryotic Gene Family. PLoS Biol. 2007, 5, e106. [Google Scholar] [CrossRef] [Green Version]
  32. Immarigeon, C.; Frei, Y.; Delbare, S.Y.N.; Gligorov, D.; Machado Almeida, P.; Grey, J.; Fabbro, L.; Nagoshi, E.; Billeter, J.-C.; Wolfner, M.F.; et al. Identification of a micropeptide and multiple secondary cell genes that modulate Drosophila male reproductive success. Proc. Natl. Acad. Sci. USA 2021, 118, e2001897118. [Google Scholar] [CrossRef] [PubMed]
  33. Aspden, J.L.; Eyre-Walker, Y.C.; Phillips, R.J.; Amin, U.; Mumtaz, M.A.S.; Brocard, M.; Couso, J.-P. Extensive translation of small Open Reading Frames revealed by Poly-Ribo-Seq. Elife 2014, 3, E03528. [Google Scholar] [CrossRef] [PubMed]
  34. Ruiz-Orera, J.; Messeguer, X.; Subirana, J.A.; Alba, M.M. Long non-coding RNAs as a source of new peptides. Elife 2014, 3, 1–24. [Google Scholar] [CrossRef] [Green Version]
  35. Samandi, S.; Roy, A.V.; Delcourt, V.; Lucier, J.-F.; Gagnon, J.; Beaudoin, M.C.; Vanderperre, B.; Breton, M.-A.; Motard, J.; Jacques, J.-F.; et al. Deep transcriptome annotation enables the discovery and functional characterization of cryptic small proteins. Elife 2017, 6, e27860. [Google Scholar] [CrossRef] [PubMed]
  36. Brunet, M.A.; Leblanc, S.; Roucou, X. Reconsidering proteomic diversity with functional investigation of small ORFs and alternative ORFs. Exp. Cell Res. 2020, 393, 112057. [Google Scholar] [CrossRef]
  37. Granzotto, A.; Lopes, F.R.; Vieira, C.; Carareto, C.M.A. Vertical inheritance and bursts of transposition have shaped the evolution of the BS non-LTR retrotransposon in Drosophila. Mol. Genet. Genom. 2011, 286, 57. [Google Scholar] [CrossRef] [PubMed]
  38. Siepel, A. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005, 15, 1034–1050. [Google Scholar] [CrossRef] [Green Version]
  39. Yang, Z. PAML 4: Phylogenetic Analysis by Maximum Likelihood. Mol. Biol. Evol. 2007, 24, 1586–1591. [Google Scholar] [CrossRef] [Green Version]
  40. Edgar, R.C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef] [Green Version]
  41. Guindon, S.; Dufayard, J.-F.; Lefort, V.; Anisimova, M.; Hordijk, W.; Gascuel, O. New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst. Biol. 2010, 59, 307–321. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Cheng, Y.; Miura, R.M.; Tian, B. Prediction of mRNA polyadenylation sites by support vector machine. Bioinformatics 2006, 22, 2320–2325. [Google Scholar] [CrossRef] [Green Version]
  43. Acevedo, J.M.; Hoermann, B.; Schlimbach, T.; Teleman, A.A. Changes in global translation elongation or initiation rates shape the proteome via the Kozak sequence. Sci. Rep. 2018, 8, 4018. [Google Scholar] [CrossRef] [Green Version]
  44. Almagro Armenteros, J.J.; Tsirigos, K.D.; Sønderby, C.K.; Petersen, T.N.; Winther, O.; Brunak, S.; von Heijne, G.; Nielsen, H. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat. Biotechnol. 2019, 37, 420–423. [Google Scholar] [CrossRef] [PubMed]
  45. Krogh, A.; Larsson, B.; von Heijne, G.; Sonnhammer, E.L. Predicting transmembrane protein topology with a hidden markov model: Application to complete genomes11Edited by F. Cohen. J. Mol. Biol. 2001, 305, 567–580. [Google Scholar] [CrossRef] [Green Version]
  46. Mészáros, B.; Erdős, G.; Dosztányi, Z. IUPred2A: Context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Res. 2018, 46, W329–W337. [Google Scholar] [CrossRef] [PubMed]
  47. Cherbas, L.; Willingham, A.; Zhang, D.; Yang, L.; Zou, Y.; Eads, B.D.; Carlson, J.W.; Landolin, J.M.; Kapranov, P.; Dumais, J.; et al. The transcriptional diversity of 25 Drosophila cell lines. Genome Res. 2011, 21, 301–314. [Google Scholar] [CrossRef] [Green Version]
  48. Saari, G.; Bienz, M. The structure of the Ultrabithorax promoter of Drosophila melanogaster. EMBO J. 1987, 6, 1775–1779. [Google Scholar] [CrossRef]
  49. Kumar, M.; Gouw, M.; Michael, S.; Sámano-Sánchez, H.; Pancsa, R.; Glavina, J.; Diakogianni, A.; Valverde, J.A.; Bukirova, D.; Čalyševa, J.; et al. ELM—The eukaryotic linear motif resource in 2020. Nucleic Acids Res. 2019, 48, D296–D306. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Zanzoni, A.; Ribeiro, D.M.; Brun, C. Understanding protein multifunctionality: From short linear motifs to cellular functions. Cell. Mol. Life Sci. 2019, 76, 4407–4412. [Google Scholar] [CrossRef] [Green Version]
  51. Van Roey, K.; Uyar, B.; Weatheritt, R.J.; Dinkel, H.; Seiler, M.; Budd, A.; Gibson, T.J.; Davey, N.E. Short Linear Motifs: Ubiquitous and Functionally Diverse Protein Interaction Modules Directing Cell Regulation. Chem. Rev. 2014, 114, 6733–6778. [Google Scholar] [CrossRef]
Figure 1. Identification of altORFs in the BX-C region of Drosophila melanogaster. (A). Total number of predicted altORFs (green curve) across the 9 different filtering steps. The corresponding percentage of previously predicted altORF peptides [33,35] is indicated (red bars). (B). Criteria applied across the different filtering steps. The threshold values used for selecting most relevant altORFs were based on scores deduced from previously predicted altORF peptides (see also materials and methods). (C). Phylogeny of the 12 Drosophila species used for conservation analyses (adapted from [37]).
Figure 1. Identification of altORFs in the BX-C region of Drosophila melanogaster. (A). Total number of predicted altORFs (green curve) across the 9 different filtering steps. The corresponding percentage of previously predicted altORF peptides [33,35] is indicated (red bars). (B). Criteria applied across the different filtering steps. The threshold values used for selecting most relevant altORFs were based on scores deduced from previously predicted altORF peptides (see also materials and methods). (C). Phylogeny of the 12 Drosophila species used for conservation analyses (adapted from [37]).
Cells 10 02983 g001
Figure 2. Distribution of the predicted altORFs in the BX-C region. Each altORF is represented as a small bar. The initial (2086, upper lines) and final (48, lower lines) number of predicted altORFs is shown. altORFs that have previously been identified are highlighted in red [33] or orange [35]. lncRNAs (blue bars) and CDS (blue lines with UTRs and exons) are indicated.
Figure 2. Distribution of the predicted altORFs in the BX-C region. Each altORF is represented as a small bar. The initial (2086, upper lines) and final (48, lower lines) number of predicted altORFs is shown. altORFs that have previously been identified are highlighted in red [33] or orange [35]. lncRNAs (blue bars) and CDS (blue lines with UTRs and exons) are indicated.
Cells 10 02983 g002
Figure 3. Characterization of the ORF268. This altORF is in the 5′UTR of Ubx, in the same orientation. The putative promoter is indicated (red arrow). It is found in 5 species and is highly conserved (yellow graph below the protein sequence alignment). The 71 aas long peptide is globally ordered. It contains a signal peptide and a transmembrane helix (pink and gray shadows, respectively), as well as several ELMs of different types. This altORF has previously been described in a pioneer study of the Ubx genomic region [48].
Figure 3. Characterization of the ORF268. This altORF is in the 5′UTR of Ubx, in the same orientation. The putative promoter is indicated (red arrow). It is found in 5 species and is highly conserved (yellow graph below the protein sequence alignment). The 71 aas long peptide is globally ordered. It contains a signal peptide and a transmembrane helix (pink and gray shadows, respectively), as well as several ELMs of different types. This altORF has previously been described in a pioneer study of the Ubx genomic region [48].
Cells 10 02983 g003
Figure 4. Characterization of the ORF44. This altORF overlaps with the 5′UTR and first coding exon of one AbdB transcript. It is in the same orientation but in a different reading frame. This altORF was found in 4 Drosophila species. The 274 aas long predicted protein displays three disordered regions (highlighted in pink) and numerous ELMs of different types.
Figure 4. Characterization of the ORF44. This altORF overlaps with the 5′UTR and first coding exon of one AbdB transcript. It is in the same orientation but in a different reading frame. This altORF was found in 4 Drosophila species. The 274 aas long predicted protein displays three disordered regions (highlighted in pink) and numerous ELMs of different types.
Cells 10 02983 g004
Figure 5. Characterization of the ORF682. (A). This altORF overlaps with the Ubx last coding exon and the beginning of its 3′UTR, in the same orientation but in a different reading frame. ORF682 is found in 3 Drosophila species. The 60 aas long predicted protein is globally disordered and contains only two ELMs of different type. (B). A peptide sequence present in the ORF682 is found in an isoform of D. bipectinata Sex comb reduced (Scr; isoform X1) and D. melanogaster Deformed (Dfd; isoform IP14630p). These two isoforms result from a frameshift of the last part of the gene encoding the homeobox domain (black bars).
Figure 5. Characterization of the ORF682. (A). This altORF overlaps with the Ubx last coding exon and the beginning of its 3′UTR, in the same orientation but in a different reading frame. ORF682 is found in 3 Drosophila species. The 60 aas long predicted protein is globally disordered and contains only two ELMs of different type. (B). A peptide sequence present in the ORF682 is found in an isoform of D. bipectinata Sex comb reduced (Scr; isoform X1) and D. melanogaster Deformed (Dfd; isoform IP14630p). These two isoforms result from a frameshift of the last part of the gene encoding the homeobox domain (black bars).
Cells 10 02983 g005
Table 1. List of the 48 selected altORFs following the different filtering steps based on conservation, transcription, and translational marks criteria.
Table 1. List of the 48 selected altORFs following the different filtering steps based on conservation, transcription, and translational marks criteria.
NameDistribution and ConservationTranscription and Translation FeaturesPeptide Characterization
Length(aa)StrandAge(My)DrosoPhastCons_ScorePromScorePromDistKozakScoreReads%ReadsAspden et al.Samandi et al.TotalELMsDifELMsELMScoreSignal Peptide, TMhelixIUPred_structureBlastP_nr
ORF682_60+4030.9540.96−2460.6435955 yes2283 disorderedScr, Dfd
ORFas357_108-2780.7760.85−1910.874846 148144 ordered
ORFas712_215-1450.7180.98−230.538645 3213184 ordered
ORFas418_88-1050.4590.96−1430.448558 138144 18% disordered
ORFas87_46-2750.6230.81−470.7559754 54188 ordered
ORFas784_49-1460.9200.93−840.7765376 44220 ordered
ORFas430_51-1040.9210.93−160.9169082 1610936 unclear
ORFas88_194-1050.9581.00−2320.88119360 1812410 ordered
ORF942_38+4060.9860.81−480.4347798 yes54195 disordered
ORF941_37+1050.9840.81−1710.4905597 yes22228 disordered
ORF268_71+1050.7550.96−2780.59412388yesyes15103471 Signal peptide, 1 TMhelixordered5′-Ubx
ORFas449_61-4050.6990.90−1210.944977 86234 disordered
ORFas450_36-40100.9950.99−90.986651 1113 32 % disordered
ORFas803_116-1040.5440.92−790.5031064 149167 ordered
ORFas452_75-1030.4620.92−1670.825860 1591961 TMhelix7 % disordered
ORF211_48+1030.6590.84−80.643653 109989 36 % disordered
ORFas137_113-1050.6160.94−720.699965 yes2210197 ordered
ORF861_41+1050.7650.88−2020.4271489 yes88432 ordered
ORFas875_38-1050.9060.95−1650.43418598 1138 ordered
ORFas165_62-1460.9360.93−1410.7278253 6374 ordered
ORF172_80+1050.6070.97−850.7901281 108233 ordered
ORF497_109+4090.4800.91−1890.839768 179233 ordered
ORFas170_68-1040.5111.00−960.434791 1210302 ordered
ORF847_70+1040.4900.88−1300.427565 2810461 14 % disordered
ORFas175_114-40110.6280.81−1770.5031664 149132 ordered
ORF842_34+1050.8150.89−1180.762579 118465 unclear
ORFas894_152-4070.6170.93−420.4979359 139180 6 % disordered
ORFas538_57-1050.9740.93−970.6507994 551177 unclear
ORFas545_47-1050.6000.84−360.727742 44247 ordered
ORFas561_72-1030.6470.82−1120.455858yesyes861681 TMhelix25 % disordered
ORFas200_54-1050.4840.81−2780.4416100yesyes65141 ordered
ORFas566_80-1050.6820.98−2650.7341390 yes17114091 TMhelixordered
ORF459_46+1040.5710.85−2050.7136100 33131 48 % disordered
ORFas567_32-1050.5820.88−470.580886 yes77235 ordered
ORF817_49+1040.5950.84−2510.657850yesyes3366 37 % disordered
ORF52_242+1050.4310.98−930.6295150yesyes3012120 5 % disordered
ORF393_241+1050.4420.89−1590.6992763 3013153 ordered
ORF727_53+1040.5390.93−2100.5521196 yes54151 disordered
ORFas1007_30-1050.9350.98−1050.8323993 55287 ordered
ORFas293_100-1040.5230.95−1340.42718784 95651 TMhelixordered
ORFas294_34-1020.6910.95−1120.4416966 44161 ordered
ORF389_51+1430.4990.99−1290.7554046 128352 67 % disordered
ORFas650_75-1050.8391.00−2340.53811854 65965 ordered
ORF44_274+4040.9060.81−1000.81822745yes 12517522 61 % disordered
ORFas1009_75-1040.9380.98−1810.7627947 0001 TMhelixordered
ORFas296_49-1050.6970.84−10.8531796 76135 ordered
ORFas1029_39-1450.6320.90−90.965658 1131 ordered
ORF358_133+4080.4840.86−1600.7484347yes 109100 ordered
ORFs are listed in the order of their cytological location in BX-C (see also Table S1). Information given in the different columns are categorized in three classes (see also materials and methods): 1—Distribution and conservation (highlighted in light orange): - Length (in amino acids); - Strand: relative to the orientation of Ubx, abdA, and AbdB, which are on the reverse strand; - Age: deduced from the divergence time of the two most distant species in which the altORF was found. Species divergence times were retrieved from [37]; - Number of Drosophila species where the altORF can be found (see also Table S1); - PhastCons score; 2—Transcription and translation features (highlighted in medium orange): - Score of the closest upstream Promoter; - Distance of the closest upstream Promoter; - Score of the Kozak sequence; - Number of RNA-seq reads; - % of the altORF covered by RNA-seq data reads; 3—Peptide characterization (highlighted in dark orange): - The corresponding altORFs has previously been predicted (‘yes’) from [34]; - The corresponding altORFs has previously been predicted (‘yes’) from [20]; - Total number of Eukaryotic Linear Motifs (ELMs) found in the encoded alternative protein; - Total number of different types of ELMs found in the encoded alternative protein; - ELM score; - Presence of a signal peptide and/or a transmembrane (TM) helix in the encoded alternative protein; - Global prediction of ordered and disordered regions deduced from IUPred; - Peptide sequences found by BlastP in other proteins. One sequence from the altORF682 was found in the Hox proteins Deformed (Dfd) and Sex combs reduced (Scr). The altORF268 has previously been annotated in the promoter region of Ubx [48].
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Naville, M.; Merabet, S. In-Depth Annotation of the Drosophila Bithorax-Complex Reveals the Presence of Several Alternative ORFs That Could Encode for Motif-Rich Peptides. Cells 2021, 10, 2983. https://doi.org/10.3390/cells10112983

AMA Style

Naville M, Merabet S. In-Depth Annotation of the Drosophila Bithorax-Complex Reveals the Presence of Several Alternative ORFs That Could Encode for Motif-Rich Peptides. Cells. 2021; 10(11):2983. https://doi.org/10.3390/cells10112983

Chicago/Turabian Style

Naville, Magali, and Samir Merabet. 2021. "In-Depth Annotation of the Drosophila Bithorax-Complex Reveals the Presence of Several Alternative ORFs That Could Encode for Motif-Rich Peptides" Cells 10, no. 11: 2983. https://doi.org/10.3390/cells10112983

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop